A neural network system for generating a quality assurance alert is provided. A computing device analyzes a quality assurance profile. A computing device arranges data in neurons of, at least, a first layer of a neural network. A computing device generates a threshold level of prediction of quality assurance based, at least in part, on output data from a neural network. A computing device applies output data from a neural network to a regression profile to determine a probability that a quality assurance issue will occur. A computing device generates a message that includes a quality assurance evaluation based, at least, on the determined probability that the quality assurance issue will occur.
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5. The method of claim 1, wherein applying the output data to the generated regression profile to determine the probability that the quality assurance issue will occur includes generating a plot depicting a graph based, at least in part, on the forecasted amount of change in the explanatory variables and the generated regression profile.
6. The method of claim 5, wherein the determined probability that the quality assurance issue will occur is based, at least in part, on a slope of the graph.
7. The method of claim 1, wherein the determined probability that the quality assurance issue will occur is based, at least in part, on a quantity of outlying variables on the regression profile.
8. The method of claim 1, wherein the determined probability that the quality assurance issue will occur is based, at least in part, on a concentration of variables in a recognized finite area on the regression profile.
10. The method of claim 9, wherein determining that the input-weight variables from the net input data should pass through, at least, one more layer of the neural network is based, at least in part, on the summed results.
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May 29, 2019
October 18, 2022
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